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Output details

11 - Computer Science and Informatics

Open University

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Output title

Feature LDA: a supervised topic model for automatic detection of web API documentations from the web

Type

E - Conference contribution

DOI

10.1007/978-3-642-35176-1_21

Name of conference/published proceedings

The 11th International Semantic Web Conference (ISWC 2012)

Volume number

7649

Issue number

First page of article

328

ISSN of proceedings

Year of publication

2012

URL

http://oro.open.ac.uk/36021/

Number of additional authors

Additional information

<16>This publication presents the first solution to successfully discover Web APIs on the open Web. It extends Latent Dirichlet Allocation with semi-supervised features leading to a superior performance over top Machine Learning classifiers. The algorithm established in this paper is a fundamental extension to iServe, our flagship services registry that was core to the EU projects SOA4All and NoTube. This work is now central to the crawler feeding the registries of two EU projects: VPH Share (Rod Hose <d.r.hose@sheffield.ac.uk>) and COMPOSE (Benjamin Mandler <MANDLER@il.ibm.com>). It is also the basis for an international collaboration with Barcelona Supercomputing Centre (Yolanda Becerra <yolandab@ac.upc.edu>).

Interdisciplinary

Cross-referral requested

Research group

None

Citation count

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract